Demand for efficient execution of complex computational tasks (such as video transcoding and artificial intelligence operations, among others) is expanding at an ever-increasing rate. Complex computational tasks are often assigned to powerful data center servers (e.g., domain controllers), as other devices (e.g., edge servers) may lack the computing resources necessary to effectively and/or efficiently complete these demanding tasks. However, deploying and maintaining domain controllers may be expensive, and adding domain controllers to scale a data center for high-demand computing tasks may be inefficient and/or impractical, especially in high-growth points-of-presence (POPS) traditionally serviced by edge servers. Moreover, due to their general-purpose design, domain controllers may struggle with and/or inefficiently handle some highly specific and demanding tasks.
Additionally, while some traditional hardware devices may be capable of performing some operations included in these complex computational tasks, such devices may be difficult to implement in some kinds of computing devices, such as edge servers, due to physical space limitations, computing power restrictions, electrical power requirements, heating and/or cooling needs, and/or data bandwidth considerations. Therefore, the present disclosure identifies and addresses a need for improved apparatuses, systems, and methods for performing hardware acceleration of complex computational tasks.